Subjective Test Results Research Articles

Correlation between subjective and objective hearing tests after unilateral and bilateral cochlear implantation

BackgroundThere are many methods for assessing hearing performance after cochlear implantation. Standard evaluations often encompass objective hearing tests only, while patients’ subjective experiences gain importance in today’s healthcare. The aim of the current study was to analyze the correlation between subjective (self-reported questionnaires) and objective (speech perception and localization) hearing test results in adult cochlear implant (CI) users. Secondary, the correlation between subjective and objective hearing tests was compared between bilateral and unilateral CI patients.MethodsData for this study were prospectively collected as part of a multicentre randomized controlled trial. Thirty-eight postlingually deafened adult patients were randomly allocated to receive either unilateral (n = 19) or bilateral (n = 19) cochlear implantation. We used data gathered after one year of follow-up. We studied the correlation between objectively measured speech perception and localization skills on the one hand and related domains of the Speech, Spatial and Qualities of Hearing Scale (SSQ) and Nijmegen Cochlear Implant Questionnaire (NCIQ) on the other hand. We also compared these correlations between unilateral and bilateral CI users.ResultsWe found significant weak to moderate negative correlations between the subjective test results (speech domain of the SSQ and the advanced speech perception domain of the NCIQ) and the related objective speech perception in noise test results (r = −0.33 to −0.48). A significant moderate correlation was found between the subjective test results (spatial domain of the SSQ) and the related objective localization test results (r = 0.59). The correlations in the group of bilateral CI patients (r = −0.28 to −0.54) did not differ significantly from the correlations in the group of unilateral CI patients (r = 0.15 to −0.40).ConclusionsCurrent objective tests do not fully reflect subjective everyday listening situations. This study elucidates the importance and necessity of questionnaires in the evaluation of cochlear implantation. Therefore, it is advised to evaluate both objective and subjective tests in CI patients on a regular basis.Trial registrationThis trial was registered on March 11, 2009 in the Dutch Trial Register. Trial registration number: NTR1722.

Mental Fatigue and Physical and Cognitive Performance During a 2-Bout Exercise Test.

The 2-bout exercise protocol has been developed to diagnose nonfunctional overreaching and the "overtraining syndrome." It consists of 2 maximal exercise bouts separated by 4hours. Mental fatigue negatively influences performance, but the effects of its occurrence during the 2-bout exercise protocol have never been investigated. The aim of this study was to examine whether mental fatigue (induced during the rest period) influences physical and cognitive performance during/after the second exercise bout of the 2-bout exercise protocol. Nine healthy, well-trained male cyclists participated in a single-blind, randomized, placebo-controlled crossover study. The intervention consisted of either 1.5-hour rest (control) or performing a computer-based Stroop task to induce mental fatigue. Cognitive (Eriksen Flanker task), physiological (lactate, maximum heart rate, and maximum wattage), and subjective data (mental fatigue-visual analog scale, Profile of Mood States, and rating of perceived exertion) were gathered. Ratings of fatigue, tension, and mental fatigue were affected in the mental fatigue condition (P < .05). Neither physiological nor cognitive differences were found between conditions. Ratings of mental fatigue were already affected after the first maximum exercise test (P < .05). Neither physical nor cognitive performance was affected by mental fatigue, but subjective ratings did reveal significant differences. It is recommended to exclude mentally challenging tasks during the 2-bout exercise protocol rest period to ascertain unaffected subjective test results. This study should be repeated in athletes diagnosed with nonfunctional overreaching/overtraining syndrome.

Dim infrared image enhancement based on convolutional neural network

Long-range infrared images are always suffering from dim targets and background clutters. To improve the contrast between target and background, we propose a novel infrared image enhancement approach by highlighting target and suppressing background clutters. Predicting the target and background plays a key role in improving the contrast of dim infrared images that targets are embedded by background clutters. Taking full advantage of machine learning on prediction, we design the convolutional neural network (CNN) architecture in our study. To overcome the lack of large training data, the handwritten images in MNIST dataset are employed to simulate the properties of long-rang infrared images including dim targets, background clutters and low contrast. The target and background sub-images are predicted from the original dim infrared image based on the filters in the first layer of the trained CNN. Finally, the dim infrared image is enhanced by amplifying the targets and subtracting background clutters. The results of subjective and quantitative tests prove the performance of the proposed algorithm in contrast improvement.

A data-driven speech enhancement method based on A* longest segment searching technique

This paper proposed a data-driven speech enhancement method based on the modeled long-range temporal dynamics (LRTDs). First, by extracting the Mel-Frequency Cepstral coefficient (MFCC) features from speech and noise corpora, the Gaussian Mixture Models (GMMs) of the speech and noise were trained respectively based on the expectation-maximization (EM) algorithm. Then, the LRTDs were obtained from the GMM models. Next, based on the LRTDs, a modified maximum a posterior (MAP) based adaptive longest matching segment searching (ALMSS) method derived from A* search technique was combined with the Vector Taylor Series (VTS) approximation algorithm in order to search the longest matching speech and noise segments (LMSNS) from speech and noise corpora. Finally, using the obtained LMSNS, the estimation of speech spectrum was achieved. Furthermore, a modified Wiener filter was constructed to further eliminate residual noise. The objective and subjective test results show that the proposed method outperforms the reference methods.

Quality Assessment of Perceptual Crosstalk on Two-View Auto-Stereoscopic Displays.

Crosstalk is one of the most severe factors affecting the perceived quality of stereoscopic 3D images. It arises from a leakage of light intensity between multiple views, as in auto-stereoscopic displays. Well-known determinants of crosstalk include the co-location contrast and disparity of the left and right images, which have been dealt with in prior studies. However, when a natural stereo image that contains complex naturalistic spatial characteristics is viewed on an auto-stereoscopic display, other factors may also play an important role in the perception of crosstalk. Here, we describe a new way of predicting the perceived severity of crosstalk, which we call the Binocular Perceptual Crosstalk Predictor (BPCP). BPCP uses measurements of three complementary 3D image properties (texture, structural duplication, and binocular summation) in combination with two well-known factors (co-location contrast and disparity) to make predictions of crosstalk on two-view auto-stereoscopic displays. The new BPCP model includes two masking algorithms and a binocular pooling method. We explore a new masking phenomenon that we call duplicated structure masking, which arises from structural correlations between the original and distorted objects. We also utilize an advanced binocular summation model to develop a binocular pooling algorithm. Our experimental results indicate that BPCP achieves high correlations against subjective test results, improving upon those delivered by previous crosstalk prediction models.

Single-Mode-Based Unified Speech and Audio Coding by Extending the Linear Prediction Domain Coding Mode

Unified speech and audio coding (USAC) is one of the latest coding technologies. It is based on a switchable coding structure, and has demonstrated the highest levels of performance for both speech and music contents. In this paper, we propose an extended version of USAC with a single-mode of operation—which does not require a switching system—by extending the linear prediction-coding mode. The main concept of this extension is the adoption of the advantages of frequency-domain coding schemes, such as windowing and transition control. Subjective test results indicate that the proposed scheme covers speech, music, and mixed streams with adequate levels of performance. The obtained quality levels are comparable with those of USAC.

A Novel Mobility-Aware Playout Algorithm for VoIP Services

The latest explosive growth in mobile networks has resulted in an increasing interest in optimisation techniques for mobile services. Resent advances in mobile wireless networks incorporate link-layer intelligence in order to enhance the performance of network and application layers. The Media Independent Handover (MIH) standard provides a framework that can make such link-layer intelligence available to upper layers. In this paper, a novel MIH-enabled playout algorithm for Voice over Internet Protocol applications is presented that aims to compensate for the degradation of voice quality caused by handovers. To that end, link-layer triggers in conjunction with speech time-scale modification techniques are exploited to mitigate the increase in delay and jitter induced by the handover process. Results of subjective listening tests show typical gains of 0.3 on a 5-point scale of the Mean Opinion Score with respect to existing playout scheduling schemes.

Prediction of reverberance in rooms with simulated non-single-exponential sound decays

It has been known that the application of diffuse field theory to the sound field with a non-single-exponential sound decay did not comply well with listeners’ experience. Recent researches have concentrated on quantifying and controlling the non-single-exponential decay processes in rooms. However, the effect of non-single-exponential sound decay on listeners’ reverberance has not been clearly known in spite of its importance. The present work tried to explore the relationship between the non-single-exponential decay of sound in rooms and the listener’s reverberance, and further to develop a simple way of predicting subjective reverberance caused by non-single-exponential decay processes. A series of listening experiments were carried out with various computer generated non-single-exponential sound decay patterns using a two alternative forced choice (2AFC) paired comparison method. A simple way of predicting listeners’ reverberance for non-single-exponential sound decays was proposed by combining the results of subjective tests and the analysis of Schroeder decay curves using decay rates at multiple fixed intervals and their effects on listeners’ reverberance. The correlation analyses suggested that the proposed method could predict listeners’ reverberance caused by non-single-exponential sound decays better than conventional parameters within the range of non-single-exponential decay patterns examined in the present work.

A two-stage noise source identification technique based on a farfield random parametric array.

A farfield random array is implemented for noise source identification. Microphone positions are optimized, with the aid of the simulated annealing method. A two-stage localization and separation algorithm is devised on the basis of the equivalent source method (ESM). In the localization stage, the active source regions are located by using the delay-and-sum method, followed by a parametric localization procedure, stochastic maximum likelihood algorithm. Multidimensional nonlinear optimization is exploited in the bearing estimation process. In the separation stage, source amplitudes are extracted by formulating an inverse problem based on the preceding source bearings identified. The number of equivalent sources is selected to be less than that of microphones to render an overdetermined problem which can be readily solved by using the Tikhonov regularization. Alternatively, the separation problem can be augmented into an underdetermined problem which can be solved by using the compressive sensing technique. Traditionally, farfield arrays only give a relative distribution of source field. However, by using the proposed method, the acoustic variables including sound pressure, particle velocity, sound intensity, and sound power can be calculated based on ESM. Numerical and experimental results of several objective and subjective tests are presented.

Childhood Obesity Is a High-risk Factor for Hypertriglyceridemia: A Case-control Study in Vietnam.

ObjectivesTo investigate the relationship between dyslipidemia and obesity status among Viet-namese adolescents.MethodsIn this case-control study, 282 adolescents (6–11 years), including 88 obese cases and 194 normal-weight controls, were recruited from a population-based cross-sectional study from two provinces in Vietnam. The anthropometric, blood lipid, and other laboratory test results of the study subjects were analyzed.ResultsObese children tended to have more visceral fat (Pearson’s r = 0.795, p < 0.0001) than subcutaneous fat (Pearson’s r = 0.754, p < 0.0001), and this difference was associated with an increase in blood triglyceride level (Pearson’s r = 0.232, p < 0.05) and a strikingly high rate of hypertriglyceridemia (38.6%). We also found that birth weight and parental body mass index were related to the status of obesity among the study subjects. However, only birth weight was significantly higher in the obese group than in the normal weight group. These findings indicate the effect of prenatal nutrition on childhood obesity. Furthermore, high-birth weight children had a surprisingly high rate of obesity.ConclusionTogether, our data suggest that obesity increased the risk for hypertriglyceridemia, which was, at least partially, due to prenatal nutrition.

MultiView Perceptual Disparity Model for Super MultiView Video

Super MultiView (SMV) video display is the most promising technology for 3-D glasses-free visualization. Although only a few prototypes are currently available, the research on technical and perceptual factors related to this approach is crucial. This paper presents a novel model to capture the subjective perception of SMV, called the MultiView Perceptual Disparity Model (MVPDM), by means of a parametrization of the relation between: 1) capture and scene settings, and 2) perception of speed comfort and smoothness in the viewpoint transition. The MVPDM is based on a novel parameter: the perceptual disparity, that captures appropriately the perceptual cues specific to SMV visualization. The model has been validated using the results of subjective tests on realistic SMV content as benchmark. On the one hand, the subjective results show a high correlation with the MVPDM parametrization, outperforming previous approaches. On the other hand, this test provides useful information about the parameters of the SMV sequences that should be used to guarantee satisfactory visual experience. Thus, the MVPDM constitutes a valuable tool for the design of subjective evaluation and content creation of SMV.

How to perform AMP? Cubic adjustments for improving the QoE

Adaptive Media Playout (AMP) consists of smoothly and dynamically adjusting the media playout rate to recover from undesired (e.g., buffer overflow/underflow or out-of-sync) situations. The existing AMP solutions are mainly characterized by two main aspects. The first one is their goal (e.g., keeping the buffers’ occupancy into safe ranges or enabling media synchronization). The second one is the criteria that determine the need for triggering the playout adjustments (e.g., buffer fullness or asynchrony levels). This paper instead focuses on a third key aspect, which has not been sufficiently investigated yet: the specific adjustment strategy to be performed. In particular, we propose a novel AMP strategy, called Cubic AMP, which is based on employing a cubic interpolation method to adjust a deviated playout point to a given reference. On the one hand, mathematical analysis and graphical examples show that our proposal provides superior performance than other existing linear and quadratic AMP strategies in terms of the smoothness of the playout curve, while significantly outperforming the quadratic AMP strategy regarding the duration of the adjustment period and without increasing the computational complexity. It has also been proved and discussed that higher-order polynomial interpolation methods are less convenient than cubic ones. On the other hand, the results of subjective tests confirm that our proposal provides better Quality of Experience (QoE) than the other existing AMP strategies.

A Histogram-Based Quality Model for HTTP Adaptive Streaming

HTTP Adaptive Streaming (HAS) has become a popular solution for multimedia delivery nowadays. Because of throughput variations, video quality fluctuates during a streaming session. Therefore, a main challenge in HAS is how to evaluate the overall video quality of a session. In this paper, we explore the impacts of quality values and quality variations in HAS. We propose to use the histogram of segment quality values and the histogram of quality gradients in a session to model the overall video quality. Subjective test results show that the proposed model has very high prediction performance for different videos. Especially, the proposed model provides insights into the influence factors of the overall quality, thus leading to suggestions to improve the quality of streaming video.

Thin-slice vision: inference of confidence measure from perceptual video quality

There has been considerable research on thin-slice judgments, but no study has demonstrated the predictive validity of confidence measures when assessors watch videos acquired from communication systems, in which the perceptual quality of videos could be degraded by limited bandwidth and unreliable network conditions. This paper studies the relationship between high-level thin-slice judgments of human behavior and factors that contribute to perceptual video quality. Based on a large number of subjective test results, it has been found that the confidence of a single individual present in all the videos, called speaker’s confidence (SC), could be predicted by a list of features that contribute to perceptual video quality. Two prediction models, one based on artificial neural network and the other based on a decision tree, were built to predict SC. Experimental results have shown that both prediction models can result in high correlation measures.

Improving Mandarin Prosody Generation Using Alternative Smoothing Techniques

Prosody plays a vital role for conveying both communicative meanings and specific speaking styles in speech communication. In recent years, Hidden Markov Model HMM-based synthesis system HTS has been developed in triumph, which can synthesize stable and smooth speech. However, the prosody of the synthesized speech suffers from the over-smoothing problem. Thus, a better prosodic model is required to improve the natural variability of the synthesized speech. This study exploits a hybrid method to alleviate this problem by combining the statistical and the template-based unit selection methods. First, a two-level clustering approach is proposed to obtain representative prosodic patterns denoted by codewords of the hierarchical prosodic structure modeled by a modified Fujisaki model. The prosodic codewords are then used to represent the prosody of each sentence in the parallel corpus consisting of the real speech corpus and the synthesized counterpart obtained from the HTS. The synthesized speech utterance is then used as the query for retrieving the prosodic codewords of the utterances in the synthesized corpus. The retrieved synthesized prosodic codewords are mapped to the prosodic codewords of the real speech based on linear mapping rules obtained from the parallel corpus. The prosodic codeword language models for prosodic word and prosodic phrase are employed respectively to choose the optimal codeword sequence of the real speech. Finally, the most likely sequence of prosodic codewords can be obtained based on the NURBS-based continuity measure for synthesizing speech with natural prosody. The experimental results of subjective and objective tests demonstrate that the proposed prosodic model substantially improves naturalness of the intonation of the synthesized speech compared to that of the HMM-based method.

A No Reference Video Quality Metric Based on Jerkiness Estimation Focusing on Multiple Frame Freezing in Video Streaming

ABSTRACTIn wireless networks, due to limited bandwidth and packet losses, seamless and ubiquitous delivery of high-quality video streaming services is a big challenge for the operators. In order to improve the process of online video quality monitoring, the presence of no reference (NR) objective video quality assessment (VQA) methods is required. In some networks, the video decoder on the reception side adopts a mechanism in which last correctly received frame is frozen and displayed on video display terminal until the next correct frame is received. This phenomenon, employed as an error concealment technique, can cause a perceptual jerkiness on the video display terminal. In this paper, we have proposed an enhanced model of objective VQA based on the estimation of jerkiness. A study of three contemporary NR methods, used for objective VQA and online monitoring of videos, has been included along with subjective VQA tests. The subjective tests were performed for a set of video sequences with specific spatial and temporal information. The proposed NR method is based on our careful observations from the subjective test results and our main focus is to cater the effect of multiple frame freeze impairments in video steaming. Comparison with other NR methods shows that the proposed method performs better, in terms of estimating the impact of multiple frame freezing impairments, and has more affinity with the subjective test results.

VoIP-quality of experience modeling: E-model and simplified E-model enhancement using bias factor

The E-model is a non-intrusive measurement method that many researchers have applied to the study of VoIP quality measurement. While the Simplified E-model is a modified version from the original, it can still be used as an alternative solution. Nevertheless, it has been found that the E-model and the Simplified E-model still require further improvement. Therefore, to enhance the original E-model, this paper proposes a new factor. Moreover, the Simplified E-model has also been enhanced by the same approach. Based-on the Thai environment, the new factor called Thai Bias factor, can be computed by subtracting the subjective test results using conversation tests with native Thai users from the objective test results using an E-model tool and the Simplified E-model calculation. Of course, both E-mode tests and conversation tests were conducted with the same VoIP system and test scenarios. The Enhanced E-model and the Simplified E-model using the Thai Bias factor were then evaluated by comparing the test set from other groups of native Thai users. After evaluation of the improved models, it has been found that the Enhanced E-model and the enhanced Simplified E-model can gain higher confidence. The Enhanced E-model delivers improved accuracy and reliability at approximately more than 20 % when compared to an available E-model tool, while the Enhanced Simplified E-model delivers improved performance at approximately more than 46 % when compared to Simplified E-model calculation.

Diagnostic Value of Fecal Calprotectin in Preterm Infants with Necrotizing Enterocolitis.

Necrotizing enterocolitis (NEC) is the most commonly acquired gastrointestinal emergency among neonates. However, the present diagnosis methods of NEC are non-specific and do not provide sufficient insight into the early discrimination. Fecal calprotectin (FC) is an intestinal-specific biomarker and has been used to differentiate different intestinal diseases. The aim of this study is to evaluate the value of FC as an early indicator for the identification of NEC. A total of 40 preterm infants were recruited, including 17 cases with NEC and 23 normal preterm infants. At enrollment, the clinical features, radiological finding, serological test, and other test results of subjects were recorded. FC concentration assays were performed by enzyme-linked immunosorbent assay (ELISA). The classification of the NEC was confirmed with the modified Bell staging criteria. The median FC levels in the NEC group were significantly higher than those in the non-NEC group (858 (347.5, 1417.5) vs. 179 (125,265) μg/g, p < 0.001). There was statistical difference in stage I, II, and III of NEC (χ2 = 6.672, p = 0.036), the median FC levels were 457 (309, 875), 932 (532, 1712), and 3108 (1378, 4276) μg/g, respectively. FC levels were correlated negatively to platelet counts (r = -0.491, p = 0.001), and positively to CRP (0.357, p = 0.024). The ROC curve defined a cutoff of 281 μg/g for NEC in preterm infants (Z = 11.737, p < 0.001), the area under the curve (AUC) (95% confidence interval) was 0.931 (0.804, 0.987), and the sensitivity and specificity were 88.24% (63.6%, 98.5%), 82.61% (61.2%, 95.0%), respectively. FC concentration is a useful, safe, and noninvasive test. It increases in preterm infants with NEC and has the potential to diagnose NEC early and to remind us of the severity of NEC in preterm infants.

Enhanced Maximum Voiced Frequency Estimation Scheme for HTS Using Two-Band Excitation Model

In a hidden Markov model–based speech synthesis system using a two-band excitation model, a maximum voiced frequency (MVF) is the most important feature as an excitation parameter because the synthetic speech quality depends on the MVF. This paper proposes an enhanced MVF estimation scheme based on a peak picking method. In the proposed scheme, both local peaks and peak lobes are picked from the spectrum of a linear predictive residual signal. The average of the normalized distances of local peaks and peak lobes is calculated and utilized as a feature to estimate an MVF. Experimental results of both objective and subjective tests show that the proposed scheme improves the synthetic speech quality compared with that of a conventional one in a mobile device as well as a PC environment.

Sparse Hidden Markov Models for Speech Enhancement in Non-Stationary Noise Environments

We propose a sparse hidden Markov model (HMM)-based single-channel speech enhancement method that models the speech and noise gains accurately in non-stationary noise environments. Autoregressive models are employed to describe the speech and noise in a unified framework and the speech and noise gains are modeled as random processes with memory. The likelihood criterion for finding the model parameters is augmented with an ${l_p}$ regularization term resulting in a sparse autoregressive HMM (SARHMM) system that encourages sparsity in the speech- and noise- modeling. In the SARHMM only a small number of HMM states contribute significantly to the model of each particular observed speech segment. As it eliminates ambiguity between noise and speech spectra, the sparsity of speech and noise modeling helps to improve the tracking of the changes of both spectral shapes and power levels of non-stationary noise. Using the modeled speech and noise SARHMMs, we first construct a noise estimator to estimate the noise power spectrum. Then, a Bayesian speech estimator is derived to obtain the enhanced speech signal. The subjective and objective test results indicate that the proposed speech enhancement scheme can achieve a larger segmental SNR improvement, a lower log-spectral distortion and a better speech quality in stationary noise conditions than state-of-the-art reference methods. The advantage of the new method is largest for non-stationary noise conditions .